Browsing by Keyword "Computational Mathematics"
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Item A Blockchain-Based Audit Trail Mechanism: Design and Implementation: Design and implementation(2021-11-26) Regueiro, Cristina; Seco, Iñaki; Gutiérrez-Agüero, Iván; Urquizu, Borja; Mansell, Jason; Tecnalia Research & Innovation; CIBERSEC&DLTAudit logs are a critical component in today’s enterprise business systems as they provide several benefits such as records transparency and integrity and security of sensitive information by creating a layer of evidential support. However, current implementations are vulnerable to attacks on data integrity or availability. This paper presents a Blockchain-based audit trail mechanism that leverages the security features of Blockchain to enable secure and reliable audit trails and to address the aforementioned vulnerabilities. The architecture design and specific implementation are described in detail, resulting in a real prototype of a reliable, secure, and user-friendly audit trail mechanism.Item A deep learning approach to the inversion of borehole resistivity measurements(2020-04-13) Shahriari, M.; Pardo, D.; Picon, A.; Galdran, A.; Del Ser, J.; Torres-Verdín, C.; COMPUTER_VISION; IABorehole resistivity measurements are routinely employed to measure the electrical properties of rocks penetrated by a well and to quantify the hydrocarbon pore volume of a reservoir. Depending on the degree of geometrical complexity, inversion techniques are often used to estimate layer-by-layer electrical properties from measurements. When used for well geosteering purposes, it becomes essential to invert the measurements into layer-by-layer values of electrical resistivity in real time. We explore the possibility of using deep neural networks (DNNs) to perform rapid inversion of borehole resistivity measurements. Accordingly, we construct a DNN that approximates the following inverse problem: given a set of borehole resistivity measurements, the DNN is designed to deliver a physically reliable and data-consistent piecewise one-dimensional layered model of the surrounding subsurface. Once the DNN is constructed, we can invert borehole measurements in real time. We illustrate the performance of the DNN for inverting logging-while-drilling (LWD) measurements acquired in high-angle wells via synthetic examples. Numerical results are promising, although further work is needed to achieve the accuracy and reliability required by petrophysicists and drillers.